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SmolMath-135M/README.md
ModelHub XC 7a3cc858d5 初始化项目,由ModelHub XC社区提供模型
Model: Ashed00/SmolMath-135M
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2026-05-26 23:27:57 +08:00

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---
library_name: transformers
license: apache-2.0
datasets:
- Ashed00/combined_math_problems
- openai/gsm8k
- deepmind/aqua_rat
base_model:
- HuggingFaceTB/SmolLM2-135M
---
# SmolMath-135M
SmolMath is a full finetuned version of SmolLM2-135M parameter, trained to obtain the highest math accuracy, with least drop in other text benchmarks.
**Important**: All training codes are present in the [Github](https://github.com/Ashu-00/SmolMath/)
**Important**: Please refer to the [Blog](https://hackmd.io/@ashu-00/SmolMath) for methodology and Training details.
## Usage
```python
model_path = "Ashed00/SmolMath-135M" # Path where your fine-tuned model is saved
from transformers import pipeline
pipe = pipeline("text-generation", model=model_path)
question = "What is 2+2?"
prompt = "Question: " + question + "\nAnswer:"
output = pipe(
prompt,
max_length=100,
do_sample=False, # disable sampling for greedy decoding
)[0]["generated_text"]
```
## Evaluation and Performance
### Comparision with Base Model
| **Metrics** | **SmolLM2-135M-8k** | **SmolMath-135M** | **Δ (Change)** |
|-------------------|---------------------|--------------------|----------------|
| HellaSwag | 42.1 | 41.15 | 0.95 |
| PIQA | 68.4 | 63.55 | 4.85 |
| CommonsenseQA | 33.9 | 33.42 | 0.48 |
| TriviaQA | 4.1 | 0.0 | 4.10 |
| Winogrande | 51.3 | 51.78 | +0.48 |
| OpenBookQA | 34.6 | 30.80 | 3.80 |
| GSM8K (0-shot)* | 0.0 | 6.9 | +6.90 |
*This was evaluated using the lighteval script, which is favoured by the SmolLM2 creators in their evaluation and varies from the SmolMath prompt structure.
### Math Benchmarks
| Model | AddSub* (%) | MAWPS** (%) | GSM8K* (%) |
|----------------------|------------|-----------|-----------|
| apple/OpenELM-270M-Instruct | 2.14 | 2.83 | 2.05 |
| HuggingFaceTB/SmolLM2-135M-Instruct | 1.52 |4.04 | 0.45 |
| SmolMath-no GRPO (ours) | 9.64 | 7.47 | 6.22 |
| SmolMath (ours) | **12.05** | **8.31** | **7.51** |
*Evaluated only on the test set, not included in the training
**Evaluated on complete dataset, not included in the training
## Citation
Incase you want to use this model in your work, you can site us.
```
@misc{SmolMath,
title = {Building SmolMath: A Math Reasoning SLM Under 150M Parameters},
url = {https://hackmd.io/@ashu-00/SmolMath},
author = {ashu-00},
month = {July},
year = {2025}
}
```